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ORCIDDongmian Zou
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2020 – today
- 2024
[j5]Yifei Yang
, Peng Wang, Xiaofan He, Dongmian Zou:
GRAM: An interpretable approach for graph anomaly detection using gradient attention maps. Neural Networks 178: 106463 (2024)- [j4]Hongfei Wang, Ziqiang Zhang, Hongcan Xiong, Dongmian Zou, Yu Chen, Hai Jin:
GRAND: A Graph Neural Network Framework for Improved Diagnosis. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(4): 1288-1301 (2024) - [j3]Yifei Yang, Dongmian Zou, Xiaofan He:
Graph Neural Network-Based Node Deployment for Throughput Enhancement. IEEE Trans. Neural Networks Learn. Syst. 35(10): 14810-14824 (2024) - [c9]Yifei Yang, Wonjun Lee, Dongmian Zou, Gilad Lerman:
Improving Hyperbolic Representations via Gromov-Wasserstein Regularization. ECCV (82) 2024: 211-227 - [c8]Shanru Lin, Temirlan Sabyrbayev, Zhexu Jin, Gaoyang Li, Huansheng Cao, Dongmian Zou:
TopoUT: Enhancing Cell Segmentation Through Efficient Topological Regularization. ISBI 2024: 1-5 - [c7]Yuekang Li, Yidan Mao, Yifei Yang, Dongmian Zou:
Improving Robustness of Hyperbolic Neural Networks by Lipschitz Analysis. KDD 2024: 1713-1724 - [i15]Jing Gu, Dongmian Zou:
Three Revisits to Node-Level Graph Anomaly Detection: Outliers, Message Passing and Hyperbolic Neural Networks. CoRR abs/2403.04010 (2024) - [i14]Yifei Yang, Wonjun Lee, Dongmian Zou, Gilad Lerman:
Improving Hyperbolic Representations via Gromov-Wasserstein Regularization. CoRR abs/2407.10495 (2024) - 2023
- [j2]Rui Jiang, Yijia Xue, Dongmian Zou:
Interpretability-Aware Industrial Anomaly Detection Using Autoencoders. IEEE Access 11: 60490-60500 (2023) - [c6]Yinglong Guo, Dongmian Zou, Gilad Lerman:
An Unpooling Layer for Graph Generation. AISTATS 2023: 3179-3209 - [c5]Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman:
Robust Variational Autoencoding with Wasserstein Penalty for Novelty Detection. AISTATS 2023: 3538-3567 - [c4]Yaning Jia, Dongmian Zou, Hongfei Wang, Hai Jin:
Enhancing Node-Level Adversarial Defenses by Lipschitz Regularization of Graph Neural Networks. KDD 2023: 951-963 - [c3]Jing Gu, Dongmian Zou:
Three Revisits to Node-Level Graph Anomaly Detection: Outliers, Message Passing and Hyperbolic Neural Networks. LoG 2023: 14 - [i13]Eric Qu, Dongmian Zou:
Hyperbolic Convolution via Kernel Point Aggregation. CoRR abs/2306.08862 (2023) - [i12]Wonjun Lee, Yifei Yang, Dongmian Zou, Gilad Lerman:
Monotone Generative Modeling via a Gromov-Monge Embedding. CoRR abs/2311.01375 (2023) - [i11]Yifei Yang, Peng Wang, Xiaofan He, Dongmian Zou:
Interpretable Graph Anomaly Detection using Gradient Attention Maps. CoRR abs/2311.06153 (2023) - 2022
- [i10]Eric Qu, Dongmian Zou:
Hyperbolic Neural Networks for Molecular Generation. CoRR abs/2201.12825 (2022) - [i9]Yinglong Guo, Dongmian Zou, Gilad Lerman:
An Unpooling Layer for Graph Generation. CoRR abs/2206.01874 (2022) - [i8]Yifei Yang, Dongmian Zou, Xiaofan He:
Graph Neural Network Based Node Deployment for Throughput Enhancement. CoRR abs/2209.06905 (2022) - 2020
- [j1]Dongmian Zou, Radu V. Balan, Maneesh Singh:
On Lipschitz Bounds of General Convolutional Neural Networks. IEEE Trans. Inf. Theory 66(3): 1738-1759 (2020) - [c2]Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman:
Robust Subspace Recovery Layer for Unsupervised Anomaly Detection. ICLR 2020 - [i7]Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman:
Novelty Detection via Robust Variational Autoencoding. CoRR abs/2006.05534 (2020)
2010 – 2019
- 2019
- [c1]Dongmian Zou, Gilad Lerman:
Encoding robust representation for graph generation. IJCNN 2019: 1-9 - [i6]Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman:
Robust Subspace Recovery Layer for Unsupervised Anomaly Detection. CoRR abs/1904.00152 (2019) - 2018
- [i5]Dongmian Zou, Gilad Lerman:
Graph Convolutional Neural Networks via Scattering. CoRR abs/1804.00099 (2018) - [i4]Dongmian Zou, Radu V. Balan, Maneesh Singh:
On Lipschitz Bounds of General Convolutional Neural Networks. CoRR abs/1808.01415 (2018) - [i3]Dongmian Zou, Gilad Lerman:
Graph Generation via Scattering. CoRR abs/1809.10851 (2018) - 2017
- [b1]Dongmian Zou:
Nonlinear Analysis of Phase Retrieval and Deep Learning. University of Maryland, College Park, MD, USA, 2017 - [i2]Radu V. Balan, Maneesh Singh, Dongmian Zou:
Lipschitz Properties for Deep Convolutional Networks. CoRR abs/1701.05217 (2017) - 2014
- [i1]Radu V. Balan, Dongmian Zou:
Phase Retrieval using Lipschitz Continuous Maps. CoRR abs/1403.2301 (2014)
Coauthor Index
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